The following pages link to (Q4250973):
Displaying 33 items.
- Dispatching rule selection with Gaussian processes (Q301496) (← links)
- GP-DEMO: differential evolution for multiobjective optimization based on Gaussian process models (Q319093) (← links)
- Multi-output local Gaussian process regression: applications to uncertainty quantification (Q385889) (← links)
- Fast approximate Bayesian computation for estimating parameters in differential equations (Q517372) (← links)
- A belief function theory based approach to combining different representation of uncertainty in prognostics (Q528771) (← links)
- Bayesian quantile regression for single-index models (Q892421) (← links)
- A framework for optimization under limited information (Q1945509) (← links)
- Robust weighted Gaussian processes (Q1995846) (← links)
- Emulating dynamic non-linear simulators using Gaussian processes (Q2002727) (← links)
- When and why PINNs fail to train: a neural tangent kernel perspective (Q2136450) (← links)
- Physics-informed cokriging: a Gaussian-process-regression-based multifidelity method for data-model convergence (Q2222351) (← links)
- Iterative construction of Gaussian process surrogate models for Bayesian inference (Q2301102) (← links)
- Graph kernels and Gaussian processes for relational reinforcement learning (Q2433177) (← links)
- Additive regularization trade-off: fusion of training and validation levels in kernel methods (Q2491372) (← links)
- Data-driven facial animation based on manifold Bayesian regression (Q2508193) (← links)
- Bayesian approach to feature selection and parameter tuning for support vector machine classifiers (Q2568024) (← links)
- Nonparametric identification of population models via Gaussian processes (Q2641783) (← links)
- Variational Gaussian process for optimal sensor placement. (Q2662468) (← links)
- Lectures on Gaussian Processes (Q3102760) (← links)
- Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data (Q3119847) (← links)
- Warped Gaussian Processes and Derivative-Based Sequential Designs for Functions with Heterogeneous Variations (Q3176256) (← links)
- Smooth Random Functions, Random ODEs, and Gaussian Processes (Q4621288) (← links)
- (Q4998866) (← links)
- Bankruptcy Prediction: A Comparison of Some Statistical and Machine Learning Techniques (Q5198550) (← links)
- (Q5214184) (← links)
- When Bifidelity Meets CoKriging: An Efficient Physics-Informed MultiFidelity Method (Q5214833) (← links)
- Assessment of DPOAE test‐retest difference curves via hierarchical Gaussian processes (Q5347447) (← links)
- Advanced Lectures on Machine Learning (Q5424896) (← links)
- Latin hypercube designs based on strong orthogonal arrays and Kriging modelling to improve the payload distribution of trains (Q5861530) (← links)
- Priors in Bayesian Deep Learning: A Review (Q6067601) (← links)
- A singular woodbury and pseudo-determinant matrix identities and application to Gaussian process regression (Q6105986) (← links)
- Scalable Physics-Based Maximum Likelihood Estimation Using Hierarchical Matrices (Q6177922) (← links)
- Some models are useful, but how do we know which ones? Towards a unified Bayesian model taxonomy (Q6185714) (← links)
